1. Statement of the Technical Field
The invention concerns image processing, and more particularly, an image processing method for images having different spatial and spectral resolutions and including moving objects.
2. Description of the Related Art
In the field of remote image sensing, two common types of images include panchromatic imagery and multi-spectral imagery. Panchromatic imagery is imagery that is obtained by a remote sensing device with a sensor designed to detect electromagnetic energy in only one very broad band. This one very broad band typically includes most of the wavelengths of visible light. Panchromatic imagery has the advantage of offering very high spatial resolution. In contrast, multi-spectral imagery is typically created from several narrow spectral bands within the visible light region and the near infrared region. Consequently, a multi-spectral image is generally comprised of two or more image data sets, each created by sensors responsive to different portions of the optical spectrum (e.g., blue, green, red, infrared). Multi-spectral images are advantageous because they contain spectral information which is not available from a similar panchromatic image. However, multi-spectral images typically have a lower spatial resolution as compared to panchromatic images.
It is often desirable to enhance a multi-spectral image with the high resolution of a panchromatic image and vice versa. Typically this process is referred to as “fusing” of the image pair. In general, there are several requirements for successfully accomplishing the fusing process, such as the registration of the image pair. The registration process involves a determination of where each pixel in the panchromatic image maps to a location in the multi-spectral image. This process must generally be accomplished with great accuracy for best results. For example, it is desirable for each pixel in the panchromatic image to be mapped to the multi-spectral image with an accuracy of less than 0.1 panchromatic pixel radius. Registration is typically accomplished via the use of metadata associated with the images that specifies the geographic location being imaged. In addition, other registration processes are typically used to account for differences in the imaged geographic location due to variations in sensor position and acquisition time. However, such registration methods generally fail to account for moving objects in the image pair, such as clouds, aircraft, watercraft, and ground vehicles, resulting in errors in the final fused image. Therefore, what is needed are systems and methods for registration and fusion of image pairs that take into account moving objects.